1. Alejandro García Macías
Measuring Individual Social Capital from a Personal Networks approach: Limits and possibilities.
Alejandro García Macías
Universidad Autónoma de Barcelona
Universidad Autónoma de Aguascalientes

2. The research
This PhD thesis at UAB (directed by Lozares, Carlos, and Molina, José Luis) is part of a multidisciplinary research project for the thematic network “Poverty and territorial development” of the National Council of Science and technology (CONACYT) in México.

3. Objective
Among others, we want to measure and analyze Social Capital of productive actors in three high-specialized towns in central-western México, departing from the structural composition and occupational attributes of their personal networks.

4. Social Capital
“One of the most successful ‘exports’ from sociology to other social sciences and to public discourse ”(Portes, 2000).
Fast and growing spread and multiple approaches: conceptual chaos.

5. A clear premise can be drawn (as in Bourdieu, Coleman, Portes, Putnam, Burt, etc.):
“It inheres and derives from Social Networks”.
In my research I take the real network approach, instead of the metaphorical one.

7. Two main notions in estimating Social Capital from a relational approach:
From the characteristics of network composition and structure (as in Granovetter, Burt, etc.)
From the unequal access of actors to resources embedded in Social Networks (as in Lin and his collegues).
For different analytical processes, different instruments: Name Generators/Interpreters, and Position (or resources) Generators.

8. Social Capital in Lin’s Theory
Social structure as hierarchical pyramid.
Actors occupy different positions and access to differentiated resources according to them.
Actors have instrumental or expressive goals and they take actions in order to reach them.
Personal relationships allow access to the resources of other actors, embedded in the network.

9. Thus, social Capital can be defined as Resources embedded in social networks
(Lin, 2001).

12. Position Generator methodology includes 3 indicators to measure SC:
The presence of alters
The resources of these Alters
The availability of these resorces to Ego.
It reveals the segments of personal networks that are relatively extensive, diverse, peripheral, and weakly tied to Ego (Fu, 2008).

13. PG use a sample of ordered structural positions salient in a society (Normally occupations), and ask respondents to indicate contacts, if any, in each of the positions.
Each position included in the list has a value, according to a selected Hierarchical Scale (e.g., Socioeconomic Status or Occupational Prestige).

15. From the responses, it becomes possible to construct measures of:
Range of accessibility to different hierarchical positions in the society
Extensity or heterogeneity of accessibility to different positions
Upper reachability of accessed social capital
(Lin, Fu, & Hsung, 2001, p. 63)

17. Classical PG measures:

18. But, data are finally analyzed as Ego attributes.
A structural (reticular) analysis can not be done, because Position Generator lacks of Alter-Alter ties.
In addition, do these postulates remain valid in specific settings, i.e. contexts with less occupational or social differentiation?

19. Case studies: Three high-specialized towns in apparel industry.

20. Moroleón, Guanajuato (49,000 inhabitants) has more than 900 small factories and 900 clothing stores.
Uriangato, Guanajuato (Conurbated , 59,000) has 617 factories and 1,218 stores… Locals call their city “The biggest clothing store in México”
Villa Hidalgo, Jalisco (18,700) has one store for every 24 people.

21. If we trace all this economic units in a map, it looks like this:

22. Atypical localities Productive specialization. Atypical labor model.
High migratory flows.
(García Macías 2011; Lozares, Molina, García Macías, & Maza, 2011; Maza et al., 2011)

23. Localidades atípicas
Lower social inequality levels than other towns and classic industrial poles in the region.
More equilibrated human development Level.
(García Macías 2011; Lozares, Molina, García Macías, & Maza, 2011; Maza et al., 2011)

25. Income Poverty (% of population)
Income Poverty at Guanajuato’s V sur region, 2005.
State/municipality
Population
Income Poverty (% of population)
Alimentary
Capacities
Patrimony
National
103,263,388
18.2
24.7
47.0
Guanajuato
4,893,812
18.9
26.6
51.6
Acámbaro
101,762
19.2
27.9
54.6
Coroneo
10,972
24.4
32.8
57.0
Jaral del Progreso
31,780
17.6
27.2
56.1
Jerécuaro
46,137
32.0
41.4
65.5
Moroleón
46,751
9.5
16.1
42.6
Salvatierra
92,411
18.6
26.8
52.2
Santiago Maravatío
6,389
14.6
20.5
41.0
Tarandacuao
10,252
19.3
25.4
45.3
Uriangato
53,077
11.6
19.9
50.4
Yuriria
63,447
36.4
61.7
Note. Data from CONEVAL (2006b)

26. Inequality indicators for V sur Region of Guanajuato, 2005.
State/Municipality
Gini coefficient
Income ratio between richest 10% and poorest 10%
Income ratio between richest 5% and poorest 5%
National
0.5006
27.7
52.7
Guanajuato
0.4820
24.8
46.7
Uriangato
0.3667
10.6
17.6
Jaral del Progreso
0.4022
13.6
23.6
Moroleón
0.4046
13.9
24.3
Coroneo
0.4264
15.4
26.0
Jerécuaro
0.4344
16.0
27.5
Salvatierra
0.4379
17.3
30.1
Santiago Maravatío
0.4391
17.2
29.5
Acámbaro
0.4442
18.2
32.9
Yuriria
0.4471
19.8
35.6
Tarandacuao
0.4509
19.4
34.3
Note. Data from CONEVAL (2006ª)

27. Methodological issues
A non-probabilistic sample (n=75) was designed, given by quotas (25) for each town, and driven by 5 occupational profiles
(Specific Occupations in significative major categories: Hierarchical “Occupational Division” and Employment Status)
Selection of informants was Chain-Referral type (Snowball).

29. An EgoNet interview was applied, with a fixed 30 Alteri number.
Being (n=75), it provides relational and attributive ocupational data for 2,250 Alteri.
730 basic questions, and up to 134 more, if details were needed.

30. To measure ISC, we propose a kind of mix method, by analyzing a set of Personal Networks simultaneously in the structural and the positional ways.
Personal networks are elicitated in the usual way.
Name Generator is occupationally content-free.
Name interpreter is designed with a strong occupational content.

31. Personal networks were analyzed in the traditional composition and structure ways.

32. Homophily baseline – inbreeding
(McPherson et.al 2001; Kossinets & Watts 2009; Lozares et.al 2011; García Macías y Lozares 2012)

33. Geo-Dispersion Index (Molina et.al. 2010)
1. Average distance Ego - Alter.
2. Average distance Ego – Alter - Alter.

34. And then by adapting the Position Generator Measures:
Alteri´s occupations were coded according to internationally standardized classifications and occupational prestige scales (SIOPS, ISEI).
Measures from the Position Generator method were calculated (not without some methodological considerations: next slide)
As Alter – Alter ties are available, there are new and more analytical possibilities.

35. Classical PG measures:

36. “New” measures proposed:
Size of the network: Number of Alter having an occupation (Excluding non-economic activities).
Total of redundant resources (Number of Alter occupationally similar to Ego, and their prestige volume)
Number of different accessed positions (In PG they are all different by definition).

37. Others.. Measures to be discussed during this stay at Konstanz:
Effective size of the network (Burt, Borgatti): Number of occupationally non-redundant Alter and their volume of prestige (excluding homphilous relationships).
Centrality-prestige reachability: Occupational prestige of most central actor in the network.
Accessed Degree-by-prestige index (Preliminar name: Just conceived yesterday)
Others..

38. Preliminary findings.
Classical Hypothesis and tendencies are confirmed:
Inbreeding Occupational Homophily
Social Capital is unequally distributed according to the Ego’s occupational prestige.
The more the status and occupational prestige, the more the access to potentially accesible resources.

41. And the visualization issue…
Volume of intra occupational group (bonding) social capital.
Internal cohesion.
Volume and sources of non-redundant (bridging / linking) SC.
Resources “flow” i.e. Ego “wins” or “loses” in his/her relationships?

42. Thank you.
Any question, comment or suggestion, will be very welcome.